Mobile Networks and Management. 5th International Conference, MONAMI 2013, Cork, Ireland, September 23-25, 2013, Revised Selected Papers

Research Article

Model-Free Adaptive Rate Selection in Cognitive Radio Links

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  • @INPROCEEDINGS{10.1007/978-3-319-04277-0_15,
        author={\^{A}lvaro Gonzalo-Ayuso and Jes\^{u}s P\^{e}rez},
        title={Model-Free Adaptive Rate Selection in Cognitive Radio Links},
        proceedings={Mobile Networks and Management. 5th International Conference, MONAMI 2013, Cork, Ireland, September 23-25, 2013, Revised Selected Papers},
        proceedings_a={MONAMI},
        year={2014},
        month={6},
        keywords={Cognitive radio (CR) rate control n-armed bandit problem reinforcement learning (RL)},
        doi={10.1007/978-3-319-04277-0_15}
    }
    
  • Álvaro Gonzalo-Ayuso
    Jesús Pérez
    Year: 2014
    Model-Free Adaptive Rate Selection in Cognitive Radio Links
    MONAMI
    Springer
    DOI: 10.1007/978-3-319-04277-0_15
Álvaro Gonzalo-Ayuso1,*, Jesús Pérez1,*
  • 1: University of Cantabria
*Contact email: alvaro@gtas.dicom.unican.es, jperez@gtas.dicom.unican.es

Abstract

In this work we address the rate adaptation problem of a cognitive radio (CR) link in time-variant fading channels. Every time the primary users (PU) liberate the channel, the secondary user (SU) selects a transmission rate (from a finite number of available rates) and begins the transmission of fixed sized packets until a licensed user reclaims the channel back. After each transmission episode the number of successfully transmitted packets is used by the SU to update its optimal rate selection ahead of the next episode. The problem is formulated as an n-armed bandit problem and it is solved by means of a Monte Carlo control algorithm.